Racial Capitalism in an Ethnic Minority Border Region
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract In the social, historical, and political context of Xi Jinping’s China, particular forms of racialization and racial capitalism have emerged in Altay Prefecture, the homeland of ethnic Kazakhs on China’s northwest border. This study examines the husbandry industry in Altay Prefecture to elucidate how Xi’s China has built a mode of racial capitalism through the management of Kazakh land, ethnicity, and culture. Within the framework of a case study, I employ document collection and participant observation methods to gather data that are then interpreted through critical policy analysis. The research shows that Kazakhs have been racialized based on their mobile pastoral traditions, enslaved in the “debt economy,” and exploited through husbandry policies and programs. The particular ways in which husbandry has been restructured and assimilated into Chinese industrial production chains exploit and reproduce the Kazakh-Han hierarchy and segregation. This close look at racial capitalism in Altay sheds light on the operations of Xi’s ecological civilization and war on poverty policies in an ethnic minority border region and discusses how they align with the broader geopolitics of the Belt and Road Initiative in Central Asia and Eastern Europe.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.007 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it